In order to solve the problem that the inductance parameters of permanent magnet assisted syn-chronous reluctance motor are easily affected by external disturbance

which leads to large current fluctu-ation and poor tracking accuracy

a two-vector-based model predictive current control was proposed based on parameter identification. The proposed algorithm is based on the vector action time derived from the current tracking formula. Taking the current tracking characteristics of d and q axes into consideration

a more accurate voltage vector time was obtained. Using the model reference adaptive system to identify the inductance parameters online and modify the model parameters in real time by using the identification re-sults to ensure that the inductance parameters of the controller match the actual parameters

the robust-ness of the two-vector-based model predictive current control system was improved. Finally

the feasibili-ty of the proposed algorithm is verified on the simulation platform and the experimental platform. The re-sults show that the proposed algorithm can effectively improve the current tracking static error and current fluctuation peak value when the motor parameters are mismatched

and improve the robustness of the sys-tem.